Neurodynamical computing at the information boundaries of intelligent systems*

Artificial intelligence has not yet achieved defining features of biological intelligence. Here, we synthesize disciplinary approaches to intelligence to argue that methodological and epistemic biases can be resolved by shifting from cognitivist brain-as-computer metaphors to recognizing the extended interdependence of living systems. By integrating the dynamical systems view of cognition with the distributed feedback of perceptual control, we highlight theoretical gaps in understanding neurodynamical function. Cell assemblies—conceived as reentrant energy flows, not merely identified co-firing groups—establish a physical 'base layer' for neurodynamical computing over information streams from embodiment and situated embedding. We place this base layer within evolutionarily conserved oscillatory and structural features of cortical-hippocampal networks. Our approach grounds embodied cognition in dynamical systems and perceptual control to bypass obstacles arising between artificial intelligence, cognitive science, and computational neuroscience.